• Price deals no one has priced before. • Turn a monitoring function into a decision engine. • Own the risk narrative with senior leadership. • Build the data foundation for Risk Analytics — and make it yours. • Actually use AI to change how the team works.

• Design and develop ML models for outreach personalization, including contextual bandits, reinforcement learning, and classification models. • Design and develop AI agents that generate dynamic, personalized nudge content and conversational interventions. • Design and analyze large-scale A/B tests and experimentation frameworks to evaluate ML models, data-driven signals, nudges, and content strategies. Define success metrics and ensure statistically sound experimentation practices. • Collaborate on the design of data pipelines and event schemas that feed the product, ensuring high-quality data for real-time decisioning and offline analysis. • Define and implement robust monitoring frameworks for the product, including short-term engagement metrics, longer-term retention, opt-outs, and intervention fatigue. • Lead, mentor, and grow the data scientists of the team. Set technical direction, ensure high-quality delivery, and foster strong collaboration with Product and Engineering stakeholders. • Inspire and empower others by genuinely caring for your own wellbeing and your colleagues. Bring wellbeing to the forefront of work, and create a supportive environment where everyone feels comfortable taking care of themselves, taking time off, and finding work-life wellness.

• Develop and implement data science models to enhance learning, assessment, and training platforms. • Conduct data analysis, statistical analysis, and predictive modeling to identify trends and patterns in educational data. • Develop machine learning models including logistic regression, random forest, and clustering algorithms tailored for educational purposes. • Use psychometric methods like Item Response Theory and Rasch Models to improve assessment data quality. • Create data visualizations and dashboards using Power BI and Tableau for educational stakeholders. • Work with cross-functional teams, including educators and researchers, to understand requirements and deliver insights. • Optimize ETL processes for data integration and preprocessing specific to educational datasets. • Support the development of adaptive learning systems and personalized learning experiences through data-driven approaches. • Implement and utilize Graph API and OData endpoints to integrate and analyze data from various sources. • Work with large language models (LLMs) and retrieval-augmented generation (RAG) techniques to enhance educational tools and provide personalized learning experiences. • Leverage vector databases to store and retrieve high-dimensional data efficiently.

• Design, build, and maintain predictive machine learning models • Partner with GTM teams to design and analyze controlled experiments • Execute proactive, complex analytical deep dives to discover latent user behavior • Support the interpretation of Marketing Mix Modeling results • Define, instrument, and govern a unified Key Performance Indicator (KPI) framework • Translate complex statistical findings and model outputs into compelling business narratives • Work closely with Data Engineering to ensure data quality • Provide technical guidance to peers and stakeholders